Observational studyThe lancet. Healthy longevity2021
Characterising the relationships between physiological indicators and all-cause mortality (NHANES): a population-based cohort study.
Observational study in The lancet. Healthy longevity, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Data-Driven Phenotyping Reveals Nonuniform Association Between Age and Mortality After Aortic Surgery: Retrospective Cohort Study of UK Biobank Data.JMIR aging · 2026Article
- Body weight variability as a predictor of cardiovascular outcomes in type 1 diabetes: A nationwide cohort study.Diabetes, obesity & metabolism · 2025Article
- Random survival forest for predicting the combined effects of multiple physiological risk factors on all-cause mortality.Scientific reports · 2024Article
- Characterizing Important Dietary Exposure Sources of Perfluoroalkyl Acids in Inuit Youth and Adults in Nunavik Using a Feature Selection Tool.Environmental health perspectives · 2024Article
- Dose-Response Associations of Lipid Traits With Coronary Artery Disease and Mortality.JAMA network open · 2024Article
- Decoding the exposome: data science methodologies and implications in exposome-wide association studies (ExWASs).Exposome · 2024Article
- High systemic immune-inflammation index is relevant to osteoporosis among middle-aged and older people: A cross-sectional study.Immunity, inflammation and disease · 2023Article
- Body mass index and all-cause mortality in a 21st century U.S. population: A National Health Interview Survey analysis.PloS one · 2023Article
- Sustainable nutrition and the case of vegetable oils to match present and future dietary needs.Frontiers in public health · 2023Review
- Association of Estimated Glomerular Filtration Rate with Risk of Head and Neck Cancer: A Nationwide Population-Based Study.Cancers · 2022Article
- Low total cholesterol predicts early death in children with hemophagocytic lymphohistiocytosis.Frontiers in pediatrics · 2022Article
- Re-evaluating physiological indicators for all-cause mortality.The lancet. Healthy longevity · 2021Article
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6 authors.
Funding
Abstract
backgroundMortality risk stratification based on dichotomising a physiological indicator with a cutoff point might not adequately capture increased mortality risk and might not account for non-linear associations. We aimed to characterise the linear and non-linear relationships of 27 physiological indicators with all-cause mortality to evaluate whether the current clinical thresholds are suitable in distinguishing patients at high risk for mortality from those at low risk.
methodsFor this observational cohort study of the US non-institutionalised population, we used data from adults (≥18 years) included in the 1999-2014 National Health and Nutrition Examination Survey (NHANES) linked with National Death Index mortality data collected from Jan 1, 1999, up until Dec 31, 2015. We used Cox proportional hazards regression models adjusted for age, sex, and race or ethnicity to assess associations of physiological indicators with all-cause mortality. We assessed non-linear associations by discretising the physiological indicator into nine quantiles (termed novemtiles) and by using a weighted sum of cubic polynomials (spline). We used ten-fold cross validation to select the most appropriate model using the concordance index, Nagelkerke R
findingsWe included 47 266 adults of 82 091 assessed for eligibility. 25 (93%) of 27 indicators showed non-linear associations with substantial increases compared with linear models in mortality risk (1·5-2·5-times increase). Height and 60 s pulse were the only physiological indicators to show linear associations. For example, participants with an estimated glomerular filtration rate (GFR) of less than 65 mL/min per 1·73 m
interpretationMost clinical indicators were shown to have non-linear associations with all-cause mortality. Furthermore, considering these non-linear associations can help derive reliable cutoffs to complement risk stratification and help inform clinical care delivery. Given the poor alignment with our proposed cutoffs, the current clinical thresholds might not adequately capture mortality risk.
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